{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 530,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "out=pd.read_table('csdn_blog_100.csv',sep='\\t',\n",
    "                engine='python',index_col=['_id'],header=None,names=['_id','标题','标签','时间','pv','作者','原创','c'])\n",
    "out['nlp']=''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 549,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import jieba\n",
    "import jieba.analyse\n",
    "import jieba.posseg as pseg\n",
    "import codecs\n",
    "from bs4 import BeautifulSoup\n",
    "from gensim import corpora, models, similarities\n",
    "\n",
    "# 加停用词库\n",
    "stopwords = codecs.open('../words/CNstop_words_zh.txt','r',encoding='utf8').readlines()\n",
    "stopwordlist = [ w.strip() for w in stopwords ]\n",
    "# 结巴分词后的停用词性 [标点符号、连词、助词、副词、介词、时语素、‘的’、数词、方位词、代词]\n",
    "stop_flag = ['x', 'c', 'u','d', 'p', 't', 'uj', 'm', 'f', 'r']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 532,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def tokenization(doc):\n",
    "#     结巴分词，去掉停用词\n",
    "    result = []\n",
    "    text = doc\n",
    "    words = pseg.cut(text)\n",
    "    for word, flag in words: \n",
    "        if flag not in stop_flag and word not in stopwords: \n",
    "            result.append(word)\n",
    "    return result\n",
    "\n",
    "ids=[]\n",
    "dockeys=[]\n",
    "# 100篇文档分词，保存\n",
    "for row in out.itertuples():\n",
    "    soup = BeautifulSoup(row.c,'html5lib').getText().strip()\n",
    "    ids.append(row.Index)\n",
    "    word_list = tokenization(soup)\n",
    "    dockeys.append(word_list)\n",
    "    out.loc[out.index==row[0],['nlp']] = ' '.join([w for w in word_list])\n",
    "\n",
    "out.drop(out.columns[[6]], axis=1,inplace=True)\n",
    "out.to_csv('csdn_blog_100_nlp.csv',sep='\\t')\n",
    "try:\n",
    "#     保存文档id列表\n",
    "    import pickle\n",
    "    f = open(\"./csdn_blog_ids_100.dat\", \"wb\")\n",
    "    pickle.dump(ids, f)\n",
    "    f.close()\n",
    "except Exception as e:\n",
    "    print('csdn_blog_ids_100.dat保存文件出错')\n",
    "    \n",
    "try:\n",
    "#     保存文档dockeys列表\n",
    "    import pickle\n",
    "    f = open(\"./csdn_blog_dockeys_100.dat\", \"wb\")\n",
    "    pickle.dump(dockeys, f)\n",
    "    f.close()\n",
    "except Exception as e:\n",
    "    print('csdn_blog_dockeys_100.dat保存文件出错')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 533,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from gensim import corpora, models, similarities\n",
    "# 建立词袋模型\n",
    "dictionary = corpora.Dictionary(dockeys)\n",
    "dictionary.save('csdn_blog_100.dict')\n",
    "# print(dictionary)\n",
    "# print(len(dockeys))\n",
    "# for doc in dockey:\n",
    "#     print(len(doc))\n",
    "# 生成词向量\n",
    "corpus = [dictionary.doc2bow(text) for text in dockeys]\n",
    "corpora.MmCorpus.serialize('csdn_blog_100.mm', corpus)\n",
    "# print('len',len(corpus))\n",
    "# print(doc_vectors)\n",
    "# for doc in corpus:\n",
    "#     print(len(doc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 550,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 建立TF-IDF模型\n",
    "tfidf = models.TfidfModel(corpus)\n",
    "tfidf_corpus = tfidf[corpus]\n",
    "# print(len(tfidf_corpus))\n",
    "# print(len(tfidf_vectors[0]))\n",
    "# for doc in tfidf_vectors:\n",
    "#     print(doc)\n",
    "# 持久化\n",
    "tfidf.save(\"./csdn_blog_model_100.tfidf\")\n",
    "tfidf = models.TfidfModel.load(\"./csdn_blog_model_100.tfidf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 551,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4092, 0.17394318),\n",
       " (10107, 0.13801867),\n",
       " (6112, 0.12311725),\n",
       " (4461, 0.11609715),\n",
       " (321, 0.10852387),\n",
       " (1883, 0.094831996),\n",
       " (4926, 0.093249574),\n",
       " (4137, 0.079429373),\n",
       " (12345, 0.076761037),\n",
       " (5670, 0.076752216),\n",
       " (10364, 0.07548704),\n",
       " (823, 0.070422918),\n",
       " (12111, 0.069211349),\n",
       " (2606, 0.064810753),\n",
       " (12242, 0.063527085),\n",
       " (10970, 0.062913775),\n",
       " (1823, 0.061469492),\n",
       " (4485, 0.060431741),\n",
       " (322, 0.057909347),\n",
       " (1834, 0.05714741)]"
      ]
     },
     "execution_count": 551,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 生成tf/idf模型,相似度矩阵\n",
    "index_tfidf = similarities.MatrixSimilarity(tfidf_corpus)\n",
    "index_tfidf.save('csdn_blog_100.index')\n",
    "\n",
    "def tfidfsimilarities(f,index,N=20):\n",
    "    # 求tf/idf模型,相似度\n",
    "    doc=''\n",
    "    with open(f, 'r') as f:\n",
    "        doc = f.read().replace('\\n','')\n",
    "    query=tokenization(doc)\n",
    "    query_bow=dictionary.doc2bow(query)\n",
    "    sims = index[query_bow]\n",
    "    from operator import itemgetter, attrgetter\n",
    "    return sorted(list(enumerate(sims)), key=itemgetter(1),reverse=True)[0:N]\n",
    "\n",
    "def toids(sim,ids):\n",
    "#     语料库ID转换成数据库里的_id\n",
    "    return [(ids[s[0]],s[1]) for s in sim]\n",
    "\n",
    "sim1 = tfidfsimilarities('../测试样本/1.txt',index_tfidf)\n",
    "toids(sim1,ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 579,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建LSI模型，设置主题数为10\n",
    "lsi = models.LsiModel(tfidf_corpus, id2word=dictionary, num_topics=10)\n",
    "lsi.print_topics(4)\n",
    "lsi_corpus = lsi[tfidf_corpus]\n",
    "# 生成lsi模型,相似度矩阵\n",
    "index_lsi = similarities.MatrixSimilarity(lsi_corpus)\n",
    "index_lsi.save('csdn_blog_100_lsi.index')\n",
    "\n",
    "def sim(f,Index,L,N=20):\n",
    "    # 求tf/idf模型,相似度\n",
    "    doc=''\n",
    "    with open(f, 'r') as f:\n",
    "        doc = f.read().replace('\\n','')\n",
    "    query=tokenization(doc)\n",
    "    query_bow=dictionary.doc2bow(query)\n",
    "    query = L[query_bow]\n",
    "    sims = Index[query]\n",
    "    from operator import itemgetter, attrgetter\n",
    "    return sorted(list(enumerate(sims)), key=itemgetter(1),reverse=True)[0:N]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 576,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(10982, 0.85179329),\n",
       " (1996, 0.84430254),\n",
       " (7617, 0.83874285),\n",
       " (9975, 0.80283195),\n",
       " (2872, 0.80068243),\n",
       " (3825, 0.79446274),\n",
       " (10440, 0.78203481),\n",
       " (3291, 0.78144395),\n",
       " (1999, 0.77139902),\n",
       " (10708, 0.76999611),\n",
       " (12093, 0.76862645),\n",
       " (10128, 0.76752114),\n",
       " (3000, 0.75083762),\n",
       " (4765, 0.74972397),\n",
       " (4092, 0.73884326),\n",
       " (5621, 0.69803166),\n",
       " (4137, 0.6779803),\n",
       " (7795, 0.66565019),\n",
       " (3293, 0.65692222),\n",
       " (3290, 0.65393209)]"
      ]
     },
     "execution_count": 576,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim2 = sim('../测试样本/2.txt',index_lsi,lsi)\n",
    "# sim3 = similarities('../测试样本/3.txt',index_lsi)\n",
    "# sim4 = similarities('../测试样本/4.txt',index_lsi)\n",
    "# sim5 = similarities('../测试样本/5.txt',index_lsi)\n",
    "toids(sim2,ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 609,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建LDA模型，设置主题数为10\n",
    "lda = models.LdaModel(tfidf_corpus, id2word=dictionary, num_topics=5)\n",
    "# lsi.print_topics(4)\n",
    "lda_corpus = lda[tfidf_corpus]\n",
    "# 生成lda模型,相似度矩阵\n",
    "index_lda = similarities.MatrixSimilarity(lda_corpus)\n",
    "index_lda.save('csdn_blog_100_lda.index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 610,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(12242, 0.96680576),\n",
       " (4653, 0.94866389),\n",
       " (3291, 0.94818997),\n",
       " (10084, 0.94552886),\n",
       " (9401, 0.94524658),\n",
       " (11918, 0.94314307),\n",
       " (3293, 0.94303781),\n",
       " (9446, 0.94299531),\n",
       " (11771, 0.94168556),\n",
       " (2600, 0.94094592),\n",
       " (3998, 0.94028157),\n",
       " (10982, 0.93924826),\n",
       " (7795, 0.93915576),\n",
       " (9975, 0.93859255),\n",
       " (638, 0.93847704),\n",
       " (5402, 0.93817246),\n",
       " (6112, 0.93769437),\n",
       " (2604, 0.93706495),\n",
       " (2606, 0.93669379),\n",
       " (10970, 0.9366678)]"
      ]
     },
     "execution_count": 610,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim2 = sim('../测试样本/2.txt',index_lda,lda)\n",
    "toids(sim2,ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 606,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 构建HDP模型\n",
    "hdp = models.HdpModel(tfidf_corpus, id2word=dictionary)\n",
    "# lsi.print_topics(4)\n",
    "hdp_corpus = hdp[tfidf_corpus]\n",
    "# 生成hdp模型,相似度矩阵\n",
    "index_hdp = similarities.MatrixSimilarity(hdp_corpus, num_features=hdp.m_T)\n",
    "index_hdp.save('csdn_blog_100_hdp.index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 607,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(10314, 0.1671586),\n",
       " (11083, 0.1671586),\n",
       " (321, 0.0),\n",
       " (322, 0.0),\n",
       " (638, 0.0),\n",
       " (823, 0.0),\n",
       " (1690, 0.0),\n",
       " (1796, 0.0),\n",
       " (1823, 0.0),\n",
       " (1826, 0.0),\n",
       " (1834, 0.0),\n",
       " (1883, 0.0),\n",
       " (1996, 0.0),\n",
       " (1999, 0.0),\n",
       " (2010, 0.0),\n",
       " (2014, 0.0),\n",
       " (2165, 0.0),\n",
       " (2430, 0.0),\n",
       " (2600, 0.0),\n",
       " (2601, 0.0)]"
      ]
     },
     "execution_count": 607,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim2 = sim('../测试样本/2.txt',index_hdp,hdp)\n",
    "toids(sim2,ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 618,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4092, 0.21201377),\n",
       " (4873, 0.21201377),\n",
       " (3087, 0.179215),\n",
       " (10614, 0.17920174),\n",
       " (4096, 0.15615825),\n",
       " (3541, 0.15540251),\n",
       " (3998, 0.14279126),\n",
       " (3338, 0.14110023),\n",
       " (4288, 0.13935466),\n",
       " (6960, 0.13181487),\n",
       " (2165, 0.12796322),\n",
       " (1823, 0.12772173),\n",
       " (4335, 0.12734564),\n",
       " (8543, 0.11255755),\n",
       " (7617, 0.10724392),\n",
       " (2606, 0.093235143),\n",
       " (9904, 0.088577986),\n",
       " (10466, 0.085759655),\n",
       " (10084, 0.081613101),\n",
       " (3796, 0.079113439)]"
      ]
     },
     "execution_count": 618,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim3 = sim('../测试样本/5.txt',index_hdp,hdp)\n",
    "toids(sim3,ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 602,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gensim.similarities.docsim.MatrixSimilarity at 0x15be0f048>"
      ]
     },
     "execution_count": 602,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_hdp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 603,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.          0.25042129  0.17548548  0.3157534   0.          0.          0.\n",
      "  0.          0.46536458  0.23692591  0.22600213  0.23370574  0.          0.\n",
      "  0.4101252   0.          0.          0.37101144  0.          0.\n",
      "  0.40429533  0.32936156  0.66732883  0.          0.          0.41595834\n",
      "  0.          0.          0.          0.53516012  0.38507584  0.          0.\n",
      "  0.32266441  0.29433498  0.          0.2348541   0.          0.21582232\n",
      "  0.46404773  0.46074799  0.43042082  0.22281262  0.          0.\n",
      "  0.00674771  0.40009949  0.25425535  0.          0.          0.          0.\n",
      "  0.35842648  0.36704838  0.41393816  0.43128031  0.36387736  0.4002617   0.\n",
      "  0.          0.64756173  0.32468292  0.          0.23924056  0.\n",
      "  0.29831401  0.          0.30614498  0.          0.          0.37741002\n",
      "  0.          0.          0.          0.32961953  0.21140745  0.22707471\n",
      "  0.53512001  0.40207165  0.          0.30487427  0.53516012  0.21608031\n",
      "  0.          0.          0.          0.          0.53516012  0.29214346\n",
      "  0.33127397  0.55355716  0.29247603  0.          0.          0.\n",
      "  0.13299125  0.          0.          0.59735787  0.36039278]\n",
      "[ 0.25042129  1.          0.27183509  0.          0.          0.\n",
      "  0.49053499  0.          0.38311541  0.          0.35008767  0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.41184264  0.          0.          0.          0.\n",
      "  0.          0.          0.          0.59650016  0.70347989  0.\n",
      "  0.49982202  0.5190751   0.68881559  0.          0.74298835  0.3343187   0.\n",
      "  0.          0.3630408   0.          0.          0.          0.          0.\n",
      "  0.39385325  0.          0.          0.67475462  0.          0.          0.\n",
      "  0.38024008  0.          0.57367802  0.54043239  0.          0.\n",
      "  0.48799789  0.62192011  0.          0.37059462  0.          0.64953369\n",
      "  0.53417647  0.47423267  0.          0.78235924  0.58462548  0.          0.\n",
      "  0.          0.5105958   0.86366433  0.35174918  0.          0.62282747\n",
      "  0.55338413  0.          0.          0.33471832  0.78235924  0.          0.\n",
      "  0.          0.          0.          0.61444652  0.          0.          0.\n",
      "  0.          0.          0.72888803  0.13991465  0.49237779  0.35103506\n",
      "  0.        ]\n",
      "[ 0.17548548  0.27183509  1.          0.          0.          0.\n",
      "  0.50878394  0.          0.26847237  0.66355348  0.24532782  0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.28860331  0.          0.          0.          0.\n",
      "  0.          0.          0.          0.41800413  0.          0.\n",
      "  0.35025582  0.          0.          0.          0.          0.76394755\n",
      "  0.          0.          0.25440487  0.53943533  0.          0.          0.\n",
      "  0.          0.27599704  0.          0.          0.          0.          0.\n",
      "  0.          0.92034304  0.          0.          0.          0.          0.\n",
      "  0.34196994  0.          0.          0.25969827  0.          0.          0.\n",
      "  0.33232379  0.89972693  0.          0.40968278  0.          0.          0.\n",
      "  0.35780567  0.22948514  0.24649213  0.          0.43645325  0.          0.\n",
      "  0.          0.23455758  0.          0.          0.          0.77334934\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.14436349  0.          0.          0.24599172  0.        ]\n",
      "[ 0.3157534   0.          0.          1.          0.52406532  0.28500468\n",
      "  0.24333681  0.          0.69099414  0.60165817  0.37560686  0.85820335\n",
      "  0.66756076  0.66756076  0.88101381  0.          0.          0.73632967\n",
      "  0.79212242  0.          0.88311523  0.88928074  0.44261187  0.37835246\n",
      "  0.          0.74433184  0.66756076  0.          0.          0.59001666\n",
      "  0.19203763  0.29211378  0.67320406  0.39829725  0.66312987  0.21533896\n",
      "  0.85877198  0.20910127  0.40347576  0.84412712  0.37000537  0.70031875\n",
      "  0.24565202  0.24494711  0.79879302  0.68062019  0.88445228  0.51714063\n",
      "  0.14651126  0.          0.33786783  0.66756076  0.73240286  0.99079311\n",
      "  0.18573996  0.87072802  0.40117654  0.          0.          0.66756076\n",
      "  0.36661649  0.35796452  0.          0.53652602  0.          0.32889265\n",
      "  0.          0.43275297  0.          0.          0.23019783  0.71621418\n",
      "  0.00827458  0.7496888   0.38227585  0.22880898  0.55090714  0.59814733\n",
      "  0.          0.47188944  0.88476759  0.59001666  0.38298354  0.\n",
      "  0.66756076  0.          0.23209818  0.59001666  0.32208958  0.36523119\n",
      "  0.          0.32245624  0.4541398   0.70308316  0.4541398   0.44477889\n",
      "  0.          0.62717319  0.70907855  0.39733478]\n",
      "[ 0.          0.          0.          0.52406532  1.          0.33516276\n",
      "  0.          0.          0.52990454  0.40036148  0.          0.70623124\n",
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      "  0.          0.52489495  0.14045423  0.49427667  0.42883888  0.41686547]\n",
      "[ 0.55355716  0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.83234042\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.72307205  0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  1.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.        ]\n",
      "[ 0.29247603  0.          0.          0.32245624  0.          0.          0.\n",
      "  0.          0.22266971  0.24195541  0.          0.23866689  0.          0.\n",
      "  0.41883141  0.          0.          0.37888733  0.          0.\n",
      "  0.41287777  0.3363533   0.4099825   0.          0.          0.42478836\n",
      "  0.          0.83744568  0.          0.54652059  0.          0.          0.\n",
      "  0.          0.30058318  0.          0.23983963  0.          0.\n",
      "  0.47389862  0.          0.2002186   0.79994696  0.          0.\n",
      "  0.00689095  0.40859288  0.          0.          0.          0.          0.\n",
      "  0.36603522  0.37484014  0.1720472   0.44043559  0.37160179  0.          0.\n",
      "  0.          0.33958948  0.33157533  0.          0.          0.\n",
      "  0.30464667  0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.54647958\n",
      "  0.          0.          0.3113462   0.54652059  0.          0.          0.\n",
      "  0.          0.          0.54652059  0.29834512  0.33830631  0.          1.\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.37861437  0.36804324]\n",
      "[ 0.          0.          0.          0.4541398   0.          0.\n",
      "  0.53581917  0.          0.          0.          0.82707322  0.          0.\n",
      "  0.          0.          0.          0.          0.72067618  0.71187687\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.62918007  0.          0.          0.          0.          0.          0.\n",
      "  0.92544842  0.          0.          0.47416887  0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.43614537\n",
      "  0.01260895  0.          0.          0.          0.          0.          0.\n",
      "  0.74258167  0.45042932  0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.88064057\n",
      "  0.          0.82923418  0.          0.50382942  0.          0.          0.\n",
      "  0.          0.          0.          0.84331638  0.          0.          0.\n",
      "  0.5110721   0.          0.          0.          0.          0.          1.\n",
      "  0.89628989  1.          0.          0.          0.45570993  0.          0.        ]\n",
      "[ 0.          0.          0.          0.70308316  0.34814283  0.18933201\n",
      "  0.48024932  0.          0.29934081  0.22616248  0.74129736  0.398947\n",
      "  0.4434686   0.4434686   0.28488937  0.          0.          0.64593476\n",
      "  0.94949794  0.          0.29055521  0.34953305  0.          0.25134408\n",
      "  0.          0.56392771  0.4434686   0.          0.          0.\n",
      "  0.12757289  0.19405469  0.99748862  0.26459363  0.22495204  0.42499277\n",
      "  0.39848366  0.13890848  0.26803377  0.22089183  0.24579901  0.32163683\n",
      "  0.          0.16272129  0.78997952  0.45469937  0.29451647  0.3435427\n",
      "  0.09732918  0.          0.22444963  0.4434686   0.66556841  0.65719181\n",
      "  0.          0.26256225  0.          0.          0.          0.4434686   0.\n",
      "  0.          0.          0.35642064  0.          0.          0.\n",
      "  0.28748298  0.          0.          0.15292317  0.99941796  0.0054969\n",
      "  0.9910894   0.25395042  0.45157722  0.36597422  0.0054307   0.\n",
      "  0.31348181  0.36446959  0.          0.75585592  0.          0.4434686   0.\n",
      "  0.45806876  0.          0.          0.          0.          0.\n",
      "  0.89628989  0.99999994  0.89628989  0.29547194  0.          0.68760353\n",
      "  0.19951369  0.        ]\n",
      "[ 0.          0.          0.          0.4541398   0.          0.\n",
      "  0.53581917  0.          0.          0.          0.82707322  0.          0.\n",
      "  0.          0.          0.          0.          0.72067618  0.71187687\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.62918007  0.          0.          0.          0.          0.          0.\n",
      "  0.92544842  0.          0.          0.47416887  0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.43614537\n",
      "  0.01260895  0.          0.          0.          0.          0.          0.\n",
      "  0.74258167  0.45042932  0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.88064057\n",
      "  0.          0.82923418  0.          0.50382942  0.          0.          0.\n",
      "  0.          0.          0.          0.84331638  0.          0.          0.\n",
      "  0.5110721   0.          0.          0.          0.          0.          1.\n",
      "  0.89628989  1.          0.          0.          0.45570993  0.          0.        ]\n",
      "[ 0.13299125  0.72888803  0.14436349  0.44477889  0.52305573  0.28445563\n",
      "  0.41904271  0.          0.65319592  0.33979037  0.18592112  0.59938478\n",
      "  0.66627479  0.66627479  0.42802265  0.          0.          0.\n",
      "  0.46792763  0.          0.43653509  0.5251444   0.21871734  0.37762362\n",
      "  0.          0.          0.66627479  0.          0.          0.          0.5084511\n",
      "  0.89250338  0.25243393  0.66297054  0.78139508  0.58842522  0.59868866\n",
      "  0.84340113  0.58024526  0.33187166  0.36929262  0.67603278  0.\n",
      "  0.24447525  0.59956485  0.66616881  0.44248658  0.72530806  0.14622901\n",
      "  0.          0.91363049  0.66627479  0.          0.38082755  0.20193416\n",
      "  0.39447799  0.4900682   0.4616679   0.          0.66627479  0.25916111\n",
      "  0.53127933  0.          0.73230422  0.          0.5548684   0.45632374\n",
      "  0.68377012  0.          0.6683355   0.54023153  0.31567097  0.00825864\n",
      "  0.37238184  0.65270162  0.63195384  0.73664939  0.00815918  0.33076507\n",
      "  0.94371241  0.54758531  0.          0.1777589   0.6683355   0.66627479\n",
      "  0.          0.          0.          0.          0.52489495  0.          0.\n",
      "  0.          0.29547194  0.          0.99999994  0.119523    0.84002465\n",
      "  0.48617703  0.        ]\n",
      "[ 0.          0.13991465  0.          0.          0.          0.\n",
      "  0.11212973  0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.16080607  0.          0.\n",
      "  0.11865361  0.15745401  0.          0.16983718  0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.          0.\n",
      "  0.          0.          0.15423986  0.          0.          0.          0.\n",
      "  0.          0.13113511  0.1235356   0.          0.          0.\n",
      "  0.14216261  0.          0.          0.          0.14847469  0.12210558\n",
      "  0.          0.          0.17883684  0.          0.          0.          0.\n",
      "  0.          0.12256458  0.          0.          0.          0.1264962   0.\n",
      "  0.          0.          0.17883684  0.          0.          0.          0.\n",
      "  0.          0.14045423  0.          0.          0.          0.          0.\n",
      "  0.119523    1.          0.11255097  0.          0.        ]\n",
      "[ 0.          0.49237779  0.          0.62717319  0.49417141  0.26874733\n",
      "  0.63877714  0.          0.42489934  0.32102636  0.37690547  0.56628537\n",
      "  0.62948155  0.62948155  0.40438625  0.          0.          0.3284193\n",
      "  0.76649696  0.          0.41242862  0.49614474  0.          0.35677037\n",
      "  0.          0.28672361  0.62948155  0.          0.          0.\n",
      "  0.18108337  0.84134841  0.66022998  0.37557748  0.73686564  0.77018458\n",
      "  0.56562769  0.79485267  0.38046059  0.31354493  0.34889942  0.45654741\n",
      "  0.          0.23097475  0.76521128  0.63512748  0.41805145  0.48764172\n",
      "  0.13815391  0.          0.86138511  0.62948155  0.33840185  0.56506252\n",
      "  0.          0.37269402  0.46148145  0.43473777  0.          0.62948155\n",
      "  0.          0.50028861  0.          0.5059213   0.          0.52250171\n",
      "  0.42970535  0.40806776  0.          0.62935001  0.21706681  0.69955558\n",
      "  0.00780258  0.72970831  0.36046997  0.66092074  0.51948214  0.00770861\n",
      "  0.          0.89012825  0.51734638  0.          0.38430765  0.62935001\n",
      "  0.62948155  0.          0.23290063  0.          0.          0.49427667\n",
      "  0.          0.          0.45570993  0.68760353  0.45570993  0.84002465\n",
      "  0.11255097  1.          0.28319973  0.        ]\n",
      "[ 0.59735787  0.35103506  0.24599172  0.70907855  0.35318679  0.19207507\n",
      "  0.          0.          0.93262762  0.53614312  0.31680486  0.7072624\n",
      "  0.44989362  0.44989362  0.81992984  0.          0.          0.48027956\n",
      "  0.31596223  0.          0.81813085  0.78096032  0.89238477  0.25498557\n",
      "  0.          0.53846401  0.44989362  0.          0.          0.69277239\n",
      "  0.6692121   0.19686617  0.1704528   0.72073102  0.60923201  0.\n",
      "  0.70827889  0.140921    0.57445216  0.82480854  0.24936016  0.90862143\n",
      "  0.28843412  0.16507882  0.40484858  0.45855707  0.81671798  0.70492959\n",
      "  0.0987393   0.          0.22770149  0.44989362  0.46398818  0.73229831\n",
      "  0.56217861  0.82466477  0.47104439  0.          0.          0.44989362\n",
      "  0.87206936  0.42030665  0.          0.69694668  0.          0.38617173\n",
      "  0.          0.72079545  0.          0.          0.68418384  0.21315283\n",
      "  0.00557654  0.25144613  0.71968317  0.29634634  0.68958485  0.69822985\n",
      "  0.56361526  0.31802356  0.76441413  0.69277239  0.30289665  0.\n",
      "  0.44989362  0.          0.          0.69277239  0.37818387  0.42883888\n",
      "  0.          0.37861437  0.          0.19951369  0.          0.48617703\n",
      "  0.          0.28319973  1.          0.46653357]\n",
      "[ 0.36039278  0.          0.          0.39733478  0.          0.          0.\n",
      "  0.          0.27437651  0.29814062  0.          0.29408845  0.          0.\n",
      "  0.5160895   0.          0.          0.46686989  0.          0.\n",
      "  0.50875336  0.41445893  0.50518578  0.60905206  0.          0.52342975\n",
      "  0.          0.          0.          0.67342979  0.          0.          0.\n",
      "  0.          0.37038249  0.          0.29553351  0.          0.\n",
      "  0.58394408  0.          0.24671197  0.28038087  0.          0.\n",
      "  0.00849112  0.50347346  0.          0.          0.          0.          0.\n",
      "  0.45103335  0.46188292  0.21199881  0.54271048  0.45789257  0.          0.\n",
      "  0.          0.4184466   0.40857145  0.          0.          0.73925114\n",
      "  0.37538958  0.54011708  0.          0.          0.          0.          0.\n",
      "  0.          0.          0.          0.          0.          0.6733793   0.\n",
      "  0.          0.38364485  0.67342979  0.          0.          0.          0.\n",
      "  0.          0.67342979  0.36762476  0.41686547  0.          0.36804324\n",
      "  0.          0.          0.          0.          0.          0.\n",
      "  0.46653357  0.99999994]\n"
     ]
    }
   ],
   "source": [
    "for i in index_hdp:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
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 "nbformat_minor": 2
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